We configure Mask R-CNN with a number of upgraded modules (described in §REF ) and training procedures (described in §REF ) relative to the original publication. These upgrades, developed primarily in [1]}, [2]}, [3]}, allow the model to be trained effectively from random initialization, thus enabling a meaningful from-scratch baseline. Next, we will discuss how the backbone, which would typically be a ResNet, can be replaced with a Vision Transformer.
